Papers
572 papers found
Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
Marina Knittel, Max Springer, John Dickerson et al.
Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning
Stephen McAleer, Gabriele Farina, Gaoyue Zhou et al.
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
Jonathan Schmidt, Philipp Hennig, Jörg Nick et al.
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
Mircea Petrache, Shubhendu Trivedi
Robust low-rank training via approximate orthonormal constraints
Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti et al.
Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders
Lai Wei, Muhammad Qasim Elahi, Mahsa Ghasemi et al.
Faster approximate subgraph counts with privacy
Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan et al.
Approximate inference of marginals using the IBIA framework
Shivani Bathla, Vinita Vasudevan
Reparameterization invariance in approximate Bayesian inference
Hrittik Roy, Marco Miani, Carl Henrik Ek et al.
Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
Leo Zhou, Joao Basso, Song Mei
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks
Felix Dangel, Johannes Müller, Marius Zeinhofer
Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient
Shaoqi Wang, Chunjie Yang, Siwei Lou
LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication
Xianzhi Zeng, Wenchao Jiang, Shuhao Zhang
Training Data Attribution via Approximate Unrolling
Juhan Bae, Wu Lin, Jonathan Lorraine et al.
OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations
Yao Shu, Jiongfeng Fang, Ying Tiffany He et al.
Optimal and Approximate Adaptive Stochastic Quantization
Ran Ben Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher et al.
Approximately Equivariant Neural Processes
Matthew Ashman, Cristiana Diaconu, Adrian Weller et al.
Can an AI Agent Safely Run a Government? Existence of Probably Approximately Aligned Policies
Frédéric Berdoz, Roger Wattenhofer
LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
Elias Jääsaari, Ville Hyvönen, Teemu Roos
CSPG: Crossing Sparse Proximity Graphs for Approximate Nearest Neighbor Search
Ming Yang, Yuzheng Cai, Weiguo Zheng
Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering
Anna Arutyunova, Jan Eube, Heiko Röglin et al.
Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
Yuri R. Fonseca, Caio F. L. Peixoto, Yuri F. Saporito
Computational Aspects of Bayesian Persuasion under Approximate Best Response
Kunhe Yang, Hanrui Zhang
Adaptable Pouring: Teaching Robots Not to Spill using Fast but Approximate Fluid Simulation
Tatiana Lopez-Guevara, Nicholas K Taylor, Michael U Gutmann et al.